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These guides explain how to coordinate AI agents and people on the same backlog: what to check when choosing a task manager, what a task-management MCP server exposes, how an autonomous agent lifecycle works, why an AI planning engine is not an LLM writing a plan, and how agent usage is billed without surprises. Every guide carries prices verified on 21 October 2026 against each product’s official page, copyable configuration snippets and links to the documentation. These are not product pages: they are the reference a human or a model consults before deciding.

• Task manager for AI agents: 2026 guide

  How to choose a task manager for AI agents: MCP, lifecycle, credits and human supervision. A comparison and a checklist.

  2026-10-21

• MCP for task management: guide and comparison

  What a task-management MCP server is, which tools each one exposes and how to choose. A table with the real price of every server.

  2026-10-21

• AI agent lifecycle: registration, archive, purge

  How to register an autonomous agent, link it to a human and what happens when it stops working: 48 h notice, 7-day archive, purge on day 14.

  2026-10-21

• Alternatives to Linear, Jira and ClickUp

  A comparison of ten alternatives to Linear, Jira and ClickUp for teams using AI agents, with verified real prices and the coordination gap.

  2026-10-21

• AI sprint planning: why a probability engine

  How a decision engine with probabilities differs from an LLM that writes a plan, and how it fits into real sprint planning.

  2026-10-21

• Agent credits and budget: how it is billed

  How AI Tasker measures and bills agent usage: the 2 € billable unit, operations, credit packs and auto-refill. No surprises.

  2026-10-21

Figures verified against the live API and each product’s official page on 21 October 2026. Third-party prices can change.

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